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Eye in outer space: satellite imageries of container ports can predict world stock returns

Author

Listed:
  • Honghai Yu

    (Nanjing University)

  • Xianfeng Hao

    (Nanjing University)

  • Liangyu Wu

    (Nanjing University)

  • Yuqi Zhao

    (Tongji University)

  • Yudong Wang

    (Nanjing University of Science and Technology)

Abstract

Forecasting stock returns is challenging. Traditional economic data that are available to all investors are published with lags and suffer from the problem of frequent revisions. Consequently, they often fail to forecast stock returns. For this reason, investors are increasingly interested in seeking alternative data. This paper forecasts stock returns using satellite-based information on shipping containers, which can capture economic activity in real-time. The container coverage area in each port is identified from 83,672 satellite images via the U-Net method and used as a proxy for the number of containers. Forecast combination over univariate predictive regression is used to generate return forecasts. The results indicate that the number of containers in ports can significantly predict stock index returns in 27 out of 33 countries at a daily frequency for the 2019–2021 period. An investor making use of satellite data on marine ports can, on average, receive an annualized return of 16.38%. The predictability can be explained by the predictive relationship between port container numbers and economic activity. In future studies, satellite data can be applied to monitor and forecast other economic indicators.

Suggested Citation

  • Honghai Yu & Xianfeng Hao & Liangyu Wu & Yuqi Zhao & Yudong Wang, 2023. "Eye in outer space: satellite imageries of container ports can predict world stock returns," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-16, December.
  • Handle: RePEc:pal:palcom:v:10:y:2023:i:1:d:10.1057_s41599-023-01891-9
    DOI: 10.1057/s41599-023-01891-9
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    as
    1. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    2. Sunder, Shyam, 1992. "Market for Information: Experimental Evidence," Econometrica, Econometric Society, vol. 60(3), pages 667-695, May.
    3. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    4. Kothari, S. P. & Shanken, Jay, 1997. "Book-to-market, dividend yield, and expected market returns: A time-series analysis," Journal of Financial Economics, Elsevier, vol. 44(2), pages 169-203, May.
    5. L. Kruitwagen & K. T. Story & J. Friedrich & L. Byers & S. Skillman & C. Hepburn, 2021. "A global inventory of photovoltaic solar energy generating units," Nature, Nature, vol. 598(7882), pages 604-610, October.
    6. Campbell, John Y., 1987. "Stock returns and the term structure," Journal of Financial Economics, Elsevier, vol. 18(2), pages 373-399, June.
    7. Claeskens, Gerda & Magnus, Jan R. & Vasnev, Andrey L. & Wang, Wendun, 2016. "The forecast combination puzzle: A simple theoretical explanation," International Journal of Forecasting, Elsevier, vol. 32(3), pages 754-762.
    8. John Y. Campbell, Robert J. Shiller, 1988. "The Dividend-Price Ratio and Expectations of Future Dividends and Discount Factors," The Review of Financial Studies, Society for Financial Studies, vol. 1(3), pages 195-228.
    9. Jiang Wang, 1993. "A Model of Intertemporal Asset Prices Under Asymmetric Information," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(2), pages 249-282.
    10. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    11. Theo Notteboom & Thanos Pallis & Jean-Paul Rodrigue, 2021. "Disruptions and resilience in global container shipping and ports: the COVID-19 pandemic versus the 2008–2009 financial crisis," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(2), pages 179-210, June.
    12. John Y. Campbell & John Cochrane, 1999. "Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior," Journal of Political Economy, University of Chicago Press, vol. 107(2), pages 205-251, April.
    13. Amit Goyal & Ivo Welch, 2003. "Predicting the Equity Premium with Dividend Ratios," Management Science, INFORMS, vol. 49(5), pages 639-654, May.
    14. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    15. Lutz Kilian & Nikos Nomikos & Xiaoqing Zhou, 2023. "Container Trade and the U.S. Recovery," International Journal of Central Banking, International Journal of Central Banking, vol. 19(1), pages 417-450, March.
    16. Talley, Wayne K., 2006. "An Economic Theory of the Port," Research in Transportation Economics, Elsevier, vol. 16(1), pages 43-65, January.
    17. Roland Döhrn, 2019. "Sieben Jahre RWI/ISL-Containerumschlag-Index–ein Erfahrungsbericht [Instruments of Climate Policy: Efficient Management or Failed State Intervention?]," Wirtschaftsdienst, Springer;ZBW - Leibniz Information Centre for Economics, vol. 99(3), pages 224-226, March.
    18. Mukherjee, Abhiroop & Panayotov, George & Shon, Janghoon, 2021. "Eye in the sky: Private satellites and government macro data," Journal of Financial Economics, Elsevier, vol. 141(1), pages 234-254.
    19. J. Vernon Henderson & Adam Storeygard & David N. Weil, 2012. "Measuring Economic Growth from Outer Space," American Economic Review, American Economic Association, vol. 102(2), pages 994-1028, April.
    20. Copeland, Thomas E & Friedman, Daniel, 1992. "The Market Value of Information: Some Experimental Results," The Journal of Business, University of Chicago Press, vol. 65(2), pages 241-266, April.
    21. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    22. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," The Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
    23. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
    24. Mark, Nelson C, 1995. "Exchange Rates and Fundamentals: Evidence on Long-Horizon Predictability," American Economic Review, American Economic Association, vol. 85(1), pages 201-218, March.
    25. John H. Cochrane, 2011. "Presidential Address: Discount Rates," Journal of Finance, American Finance Association, vol. 66(4), pages 1047-1108, August.
    26. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    27. Fama, Eugene F. & Schwert, G. William, 1977. "Asset returns and inflation," Journal of Financial Economics, Elsevier, vol. 5(2), pages 115-146, November.
    28. Jensen, Michael C., 1978. "Some anomalous evidence regarding market efficiency," Journal of Financial Economics, Elsevier, vol. 6(2-3), pages 95-101.
    29. Christina Zhu, 2019. "Big Data as a Governance Mechanism," The Review of Financial Studies, Society for Financial Studies, vol. 32(5), pages 2021-2061.
    30. Verrecchia, Robert E, 1982. "Information Acquisition in a Noisy Rational Expectations Economy," Econometrica, Econometric Society, vol. 50(6), pages 1415-1430, November.
    31. Bai, Xiwen & Xu, Ming & Han, Tingting & Yang, Dong, 2022. "Quantifying the impact of pandemic lockdown policies on global port calls," Transportation Research Part A: Policy and Practice, Elsevier, vol. 164(C), pages 224-241.
    32. Fama, Eugene F. & French, Kenneth R., 1989. "Business conditions and expected returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 25(1), pages 23-49, November.
    33. Pontiff, Jeffrey & Schall, Lawrence D., 1998. "Book-to-market ratios as predictors of market returns," Journal of Financial Economics, Elsevier, vol. 49(2), pages 141-160, August.
    34. Jeremy Smith & Kenneth F. Wallis, 2009. "A Simple Explanation of the Forecast Combination Puzzle," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(3), pages 331-355, June.
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